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Clustering and ontology-based information integration framework for surface subsidence risk mitigation in underground tunnels

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Abstract

Building information modeling brings a fundamental technological innovation to the traditional architecture industry, which can optimize the construction process and improve the efficiency and effectiveness of the overall building process. Based on the information exchange of heterogeneous information systems and data around different stages of the whole life cycle of a building project, this article analyses the current state of building information interoperability and proposes an ontology-based information integration framework. In addition, hierarchical clustering method is used to analyze and find risk factors for surface subsidence in an underground tunnel construction project, and the results input into the information integration framework. The proposed approach maps the industry foundation classes data and relationships to an ontology, and utilizes an ontology-based reasoning model. An ontology for the underground tunnel has been developed using Protégé and a Jena inference engine has been developed to investigate the early warning signs of ground subsidence.

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Acknowledgments

This research has been supported by Natural Science Foundation of Shanghai (Project No:15ZR1415000). In addition, Dr. Sugumaran’s research has been supported in part by a 2016 School of Business Administration Spring/Summer Research Fellowship from Oakland University.

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Authors and Affiliations

  1. Department of Information Management, SHU-UTS SILC Business School, Shanghai University, 20 Chengzhong Road, Jiading District, Shanghai, 201800, P. R. China

    Juan Du & Renzhi He

  2. Department of Decision and Information Sciences, School of Business Administration, Oakland University, Rochester, MI, 48309, USA

    Vijayan Sugumaran

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  1. Juan Du
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  2. Renzhi He
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  3. Vijayan Sugumaran
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Correspondence to Vijayan Sugumaran.

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Du, J., He, R. & Sugumaran, V. Clustering and ontology-based information integration framework for surface subsidence risk mitigation in underground tunnels. Cluster Comput 19, 2001–2014 (2016). https://doi.org/10.1007/s10586-016-0631-4

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  • DOI: https://doi.org/10.1007/s10586-016-0631-4

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